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  <title>Description of gaussSmooth</title>
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  <meta name="description" content="Applies Gaussian smoothing to a (multidimensional) image.">
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<h1>gaussSmooth
</h1>

<h2><a name="_name"></a>PURPOSE <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>Applies Gaussian smoothing to a (multidimensional) image.</strong></div>

<h2><a name="_synopsis"></a>SYNOPSIS <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="box"><strong>function [L,filters] = gaussSmooth( I, sigmas, shape, radius ) </strong></div>

<h2><a name="_description"></a>DESCRIPTION <a href="#_top"><img alt="^" border="0" src="../up.png"></a></h2>
<div class="fragment"><pre class="comment"> Applies Gaussian smoothing to a (multidimensional) image.

 Smooths the n-dimensional array I with a n-dimensional gaussian with
 standard deviations specified by sigmas.  This operation in linearly
 seperable and is implemented as such.

 USAGE
  [L,filters] = gaussSmooth( I, sigmas, [shape], [radius] )

 INPUTS
  I       - input image
  sigmas  - either n dimensional or 1 dimensional vector of standard devs
            if sigmas(n)&lt;=.3 then does not smooth along that dimension
  shape   - ['full'] shape flag 'valid', 'full', 'same', or 'smooth'
  radius  - [2.25] radius in units of standard deviation

 OUTPUTS
  L       - smoothed image
  filters - actual filters used, cell array of length n

 EXAMPLE
  load trees; I=ind2gray(X,map);
  I2 = gaussSmooth( I, 1, 'same' );
  figure(1); im(I); figure(2); im(I2);

 See also FILTERGAUSS

 Piotr's Computer Vision Matlab Toolbox      Version 2.0
 Copyright 2014 Piotr Dollar.  [pdollar-at-gmail.com]
 Licensed under the Simplified BSD License [see external/bsd.txt]</pre></div>





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